ISLKG: The Construction of Island Knowledge Graph and Knowledge Reasoning

Abstract

Islands with both land and sea characteristics provide the foundation for protecting the marine environment, preserving the ecological balance of the ocean, and fostering sustainable economic and social growth. Advanced monitoring technologies have boosted the collection of multi-source data of islands, but the isolation and insufficiency of data are harmful to the development and management of islands. To form a coherent and complete understanding of islands, it is necessary to convert the multi-source data into knowledge-based information. This paper proposes an island knowledge graph construction method based on the combination of entity dictionary and rule patterns, and builds the island knowledge graph (ISLKG) from the top to bottom. An ontology layer is initially created to standardize island knowledge, followed by the collection, transformation, and extraction of entities and relationships from multi-source data in order to construct an island knowledge graph. Then, a knowledge reasoning model based on knowledge graph embedding is used for knowledge completion, improving the ISLKG. Finally, the knowledge inference model was verified based on the constructed island knowledge graph. The results indicate that the model can effectively predict missing entities and complement the island knowledge graph.